Brunel University Research Archive(BURA) preserves and enables easy and open access to all
types of digital content. It showcases Brunel's research outputs.
Research contained within BURA is open access, although some publications may be subject
to publisher imposed embargoes. All awarded PhD theses are also archived on BURA.
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| Issue Date | Title | Author(s) |
|---|---|---|
| 2018 | Making use of external corrosion defect assessment (ECDA) data to predict DCVG %IR drop and coating defect area 10.1002/maco.201810085 | Yu, K |
| 3-Sep-2018 | Composite quantile regression for massive datasets | Jiang, R; Hu, X; Yu, K; Qian, W |
| 2019 | Heteroscedastic and Heavy-tailed Regression with Mixtures of Skew Laplace Normal Distributions | Yu, K; Doğru, FZ |